### Tit for Tat, Evolution, Game Theory and the Python Axelrod Library `pip install axelrod` [@drvinceknight](https://twitter.com/drvinceknight) {[github.com](https://github.com/Axelrod-Python/Axelrod), [gitter.im](https://gitter.im/Axelrod-Python/Axelrod)}/Axelrod-Python/Axelrod

Themes

reveal.js comes with a few themes built in:
Black (default) - White - League - Sky - Beige - Simple
Serif - Night - Moon - Solarized

- Mathematician;
- PyDiff organiser ([www.pydiff.wales](http://www.pydiff.wales/), [@pydiff](https://twitter.com/pydiff)); - PyCon UK Committee; - PyCon NA Committee; - Sustainable software institute fellow.
$$\begin{pmatrix} 3,3&0,5\\ 5,0&1,1 \end{pmatrix}$$

'This course has taught me to not trust my classmates.'
  1. Robert Axelrod
  2. 1980a: 14+1 strategies
  3. 1980b: 64+1 strategies

TODO: Sacrifice a cat


class TitForTat(Player):
    """A player starts by cooperating and then mimics previous move by opponent."""

    name = 'Tit For Tat'
    classifier = {
        'memory_depth': 1,  # Four-Vector = (1.,0.,1.,0.)
        'stochastic': False,
        'inspects_source': False,
        'manipulates_source': False,
        'manipulates_state': False
    }

    @staticmethod
    def strategy(opponent):
        return 'D' if opponent.history[-1:] == ['D'] else 'C'
					

class TestTitForTat(TestPlayer):

    name = "Tit For Tat"
    player = axelrod.TitForTat
    expected_classifier = {
        'memory_depth': 1,
        'stochastic': False,
        'inspects_source': False,
        'manipulates_source': False,
        'manipulates_state': False
    }

    def test_strategy(self):
        """Starts by cooperating."""
        self.first_play_test(C)

    def test_effect_of_strategy(self):
        """Repeats last action of opponent history."""
        self.markov_test([C, D, C, D])
        self.responses_test([C] * 4, [C, C, C, C], [C])
        self.responses_test([C] * 5, [C, C, C, C, D], [D])
					

class MindBender(MindWarper):
    """
    A player that changes the opponent's strategy by modifying the internal
    dictionary.
    """

    name = 'Mind Bender'
    classifier = {
        'memory_depth': -10,
        'stochastic': False,
        'inspects_source': False,
        'manipulates_source': True,  # changes what opponent will do
        'manipulates_state': False
    }

    @staticmethod
    def strategy(opponent):
        opponent.__dict__['strategy'] = lambda opponent: 'C'
        return 'D'
					
http://axelrod-tournament.readthedocs.io/

Outcomes

@AxelrodPython
https://axelrod-api.eu.aldryn.io/strategies/
`pip install axelrod` {[github.com](https://github.com/Axelrod-Python/Axelrod), [gitter.im](https://gitter.im/Axelrod-Python/Axelrod)}/Axelrod-Python/Axelrod